Aeroengine thrust estimation using least squares support vector regression machine

The first problem for direct thrust control is thrust estimation.A wrapper algorithm,which reduces the computational complexity and also enhances the model generalization performance,was proposed based on least squares support vector regression machine.In addition,as a surrogate of traditional covariance method,QR decomposition was utilized to build sparse model strengthening the numerical stability.Finally,a thrust estimator design was applied to validate the effectiveness and feasibility of the proposed feature selection algorithm and sparse model using QR decomposition.